OKR Grading: How to Score Your Key Results

Objectives and Key Results are only as effective as your ability to measure them. While setting ambitious goals drives growth, understanding how to grade your Key Results determines whether you're learning from your efforts or simply collecting vanity metrics. The grading process transforms OKRs from aspirational statements into actionable insights that inform future strategy.

Many startups struggle with OKR grading, either celebrating mediocre progress or demoralizing teams with unrealistic expectations. This guide will walk you through the proven 0.0-1.0 grading methodology, explain what different scores actually mean for your business, and provide practical frameworks for scoring both committed and moonshot OKRs.

Understanding the 0.0-1.0 Grading Scale

The OKR grading system uses a simple decimal scale from 0.0 to 1.0, where each increment represents measurable progress toward your Key Result. This standardized approach, popularized by Google and Intel, creates consistency across teams and enables meaningful comparisons over time.

The Basic Scale

0.0 - No Progress: You made no meaningful advancement toward the Key Result. This score indicates either a fundamental misalignment between resources and goals, or external blockers that prevented any movement.

0.3 - Minimal Progress: You achieved roughly 30% of your target. While some progress occurred, significant gaps remain between your current state and the desired outcome. This typically signals resource constraints, technical challenges, or misaligned priorities.

0.5 - Moderate Progress: You reached approximately half of your goal. This represents solid effort but indicates you either underestimated the difficulty, encountered unexpected obstacles, or need to reassess your approach.

0.7 - Strong Progress: You achieved 70% or more of your Key Result. For ambitious, stretch goals, this score represents excellent performance. It demonstrates meaningful advancement while acknowledging the inherent difficulty of transformative objectives.

1.0 - Complete Achievement: You fully met or exceeded your Key Result. For committed OKRs, this is the expected outcome. For moonshot OKRs, this might actually indicate you aimed too low.

The Nuance of Grading

Grading isn't purely mathematical. A Key Result stating "Increase monthly recurring revenue from 50K to 100K" might seem straightforward: reaching 75K equals 0.5. However, context matters enormously.

If you achieved 75K by acquiring enterprise customers with strong retention metrics, that progress might be worth grading higher than 0.5 due to the quality and sustainability of growth. Conversely, reaching 75K through discounted annual contracts that masked weak product-market fit might warrant a lower grade.

The grading conversation should examine:

• Quantitative achievement (raw numbers)
• Quality of results (sustainable vs temporary gains)
• Learning generated (insights that inform future cycles)
• Market conditions (external factors beyond team control)

What Good vs Bad Scores Actually Mean

Understanding score interpretation prevents teams from either settling for mediocrity or burning out chasing impossible targets. The meaning of a score depends entirely on the type of OKR you're grading.

For Committed OKRs

Committed OKRs represent goals you fully expect to achieve. These are typically operational objectives tied to core business functions.

Good Scores (0.8-1.0): Scores in this range indicate effective planning, resource allocation, and execution. You understood the problem space, estimated effort accurately, and delivered results. Consistently scoring 1.0 on committed OKRs might suggest you're not being ambitious enough.

Concerning Scores (0.5-0.7): These scores on committed OKRs signal problems. Perhaps resources were diverted mid-cycle, technical complexity was underestimated, or external dependencies failed. These situations demand post-mortem analysis and process improvements.

Bad Scores (0.0-0.4): Scores below 0.5 on committed OKRs represent significant failures in planning or execution. These require immediate leadership attention to understand root causes and implement corrective measures.

For Moonshot OKRs

Moonshot OKRs push boundaries and drive innovation. They're intentionally uncomfortable and have uncertain paths to achievement.

Good Scores (0.6-0.7): Counter-intuitively, these moderate scores represent excellent performance on moonshot goals. You stretched beyond comfort zones, learned valuable lessons, and made meaningful progress on transformative objectives. Google considers 0.6-0.7 the ideal range for ambitious goals.

Concerning Scores (0.9-1.0): Consistently achieving 1.0 on moonshot OKRs suggests you're not thinking big enough. These goals should feel uncomfortable and drive innovation. Perfect scores indicate your ambition level needs recalibration.

Acceptable Scores (0.3-0.5): Even lower scores can be valuable for true moonshots if significant learning occurred. Perhaps you discovered that customer segment wasn't viable, or that technical approach wouldn't scale. Failed experiments that generate insights have tremendous value.

Problematic Scores (0.0-0.2): Even for moonshots, extremely low scores warrant investigation. Did the team lack necessary resources? Was the objective poorly defined? Did priorities shift mid-cycle? Zero progress rarely generates useful insights.

Practical Scoring Examples

Example 1: SaaS Growth Metrics

Objective: Accelerate customer acquisition and expansion

Key Result 1: Increase monthly active users from 5,000 to 15,000

Actual Result: 11,000 monthly active users

Mathematical Score: 0.6 (6,000 gain vs 10,000 target)

Contextual Grading: 0.7

Reasoning: While the raw math suggests 0.6, the team discovered and optimized a viral referral loop that will compound over subsequent quarters. The quality of growth and strategic insights justify the higher grade.

Key Result 2: Achieve Net Promoter Score of 50+

Actual Result: NPS of 38

Mathematical Score: Would be negative using simple math

Contextual Grading: 0.4

Reasoning: Starting NPS was 25, so significant improvement occurred. However, the target wasn't met, and qualitative feedback revealed unresolved product issues. The moderate score reflects both progress and remaining challenges.

Example 2: Product Development

Objective: Ship game-changing collaboration features

Key Result: Launch real-time co-editing with 90% reliability score

Actual Result: Launched with 75% reliability, improved to 85% post-launch

Mathematical Score: 0.8 (based on final 85% vs 90% target)

Contextual Grading: 0.6

Reasoning: Shipping below the reliability target created customer support burden and required emergency engineering resources. While the feature launched, the quality threshold wasn't met. This grading acknowledges both the achievement and the cost of missing the reliability mark.

Example 3: Revenue Target (Committed OKR)

Objective: Hit quarterly revenue targets

Key Result: Achieve 500K in Q2 revenue

Actual Result: 475K in revenue

Mathematical Score: 0.95

Contextual Grading: 0.9

Reasoning: For a committed revenue OKR, missing the target by 5% is significant, even though progress seems strong. The high score reflects the near-achievement, but not rounding to 1.0 acknowledges this was a commitment that wasn't fully met.

Moonshot vs Committed OKRs: Different Grading Philosophies

The distinction between moonshot and committed OKRs fundamentally changes how you approach grading.

Committed OKRs: Precision Execution

Committed OKRs function like contracts. When you commit to achieving 100K in monthly recurring revenue or shipping three major features, stakeholders plan around these commitments.

Grading Philosophy: Binary thinking with small tolerance for variance. Scores should cluster around 0.9-1.0. Anything below 0.8 requires explanation and often indicates systemic issues.

Common Committed OKR Types:

• Revenue and financial targets
• Product launches with fixed deadlines
• Compliance or regulatory requirements
• Core operational metrics (uptime, support response times)
• Contractual obligations to customers

Grading Best Practices:

• Set realistic targets based on historical data
• Include buffers for unexpected challenges
• Track progress weekly to enable course correction
• Escalate immediately when achievement seems at risk
• Grade harshly; 0.7 on a committed OKR is a failure worth analyzing

Moonshot OKRs: Innovation and Learning

Moonshot OKRs drive breakthrough thinking. They should make teams uncomfortable and require novel approaches.

Grading Philosophy: Value creation over achievement. A 0.6 that generates transformative insights beats a 1.0 on an insufficiently ambitious goal.

Common Moonshot OKR Types:

• Market expansion into new verticals
• Revolutionary product features
• 10x improvement goals
• Entering new business models
• Technical innovations without clear paths

Grading Best Practices:

• Expect scores between 0.3-0.7
• Weight learning and insights heavily
• Celebrate intelligent failures
• Upgrade goals mid-cycle if achievement seems certain
• Grade generously; 0.3 with major learnings has real value

The 70-30 Rule

Many successful startups use a 70-30 split: 70% committed OKRs that keep the business running, 30% moonshots that drive transformation. This balance ensures operational excellence while pursuing breakthrough opportunities.

Your overall OKR portfolio health can be assessed by examining this distribution and the corresponding grade patterns.

Grading Best Practices and Common Mistakes

Best Practices

1. Grade With the Team, Not To the Team

Grading should be collaborative. The team executing the OKR has context that leadership lacks. Facilitate a grading conversation rather than dictating scores.

Effective grading sessions:

• Review quantitative results first
• Discuss qualitative factors and learnings
• Consider external factors and market conditions
• Reach consensus on final score
• Document reasoning for future reference

2. Separate Grading From Performance Reviews

Low OKR scores should not automatically translate to negative performance reviews. This separation encourages honest grading and ambitious goal-setting. If teams fear punishment for missing moonshot OKRs, they'll sandbag by setting conservative goals.

3. Track Grading Trends Over Time

A single quarter's scores tell you little. Patterns reveal much. Consistently scoring 1.0 suggests insufficient ambition. Persistently scoring below 0.3 indicates misalignment between resources and goals.

4. Document Grading Rationale

Record why you assigned each score. This documentation helps future teams understand your reasoning and creates organizational learning.

5. Use Grading to Inform Next Cycle Planning

Grading isn't the endpoint; it's the input for better future OKRs. Low scores might indicate you need different resources, revised strategies, or more realistic targets.

Common Mistakes

Mistake 1: The Generosity Trap

Teams often grade themselves too generously, inflating scores to appear successful. This destroys the learning value of OKRs and creates false confidence.

Solution: Require teams to defend their grades with specific evidence. Leadership should occasionally challenge inflated scores respectfully.

Mistake 2: Pure Mathematical Grading

Reducing every Key Result to simple arithmetic ignores context and quality.

Example: A Key Result to "acquire 1,000 new customers" achieved 600 acquisitions. Pure math suggests 0.6. But if 500 of those customers came from a problematic channel with 80% churn, while 100 came from a sustainable channel with strong retention, context matters enormously.

Solution: Use quantitative achievement as the starting point, then adjust based on quality, sustainability, and learning.

Mistake 3: Avoiding Difficult Conversations

Low scores feel uncomfortable. Teams sometimes avoid grading honestly to prevent difficult discussions.

Solution: Normalize low scores on moonshots. Celebrate the learning from intelligent failures. Reserve concern for low scores on committed OKRs.

Mistake 4: Grading in Isolation

Individual Key Result grades mean little without understanding the broader context of interconnected goals.

Solution: Grade complete Objectives (all Key Results together) and look for patterns across the OKR portfolio.

Mistake 5: Changing Definitions Mid-Cycle

Shifting what constitutes success after you see results is intellectually dishonest and destroys trust.

Solution: Lock Key Result definitions at cycle start. If circumstances change dramatically, acknowledge it explicitly and decide whether to retire the OKR rather than redefining success criteria.

When and How to Adjust Targets

The question of adjusting OKR targets mid-cycle creates philosophical debates in many organizations. The answer depends on your OKR maturity and the specific situation.

When Adjustment Makes Sense

Major Market Shifts: If external conditions fundamentally change (economic crisis, new regulation, competitive disruption), rigid adherence to outdated OKRs wastes resources.

Example: A travel startup's growth OKRs became meaningless during pandemic lockdowns. Adjusting to focus on survival and product pivots made strategic sense.

Discovery of Invalid Assumptions: Sometimes you learn that a Key Result was based on incorrect data or assumptions.

Example: You set a Key Result to "achieve 40% conversion rate on new checkout flow" based on industry benchmarks. After launch, you discovered your product complexity makes 25% conversion excellent performance. Adjusting the target acknowledges reality.

Resource Reallocation: If the company makes strategic decisions that remove resources from an OKR, maintaining the original target becomes demotivating theater.

When to Hold Firm

Uncomfortable Progress: If a moonshot OKR feels difficult but remains achievable, that discomfort is the point. Don't adjust targets simply because they're challenging.

Short-Term Setbacks: Temporary obstacles shouldn't trigger target changes. OKRs span full quarters; early struggles often precede late breakthroughs.

Political Pressure: Sometimes teams lobby to lower targets to ensure high scores. This gaming destroys OKR value.

The Adjustment Process

1. Transparently Document Reasons: Write down exactly why adjustment is necessary. Vague justifications like "it's too hard" don't suffice.

2. Leadership Approval: Target changes should require explicit leadership sign-off to prevent casual adjustments.

3. Record Original and Revised Targets: During grading, show both targets and explain which you're grading against.

4. Limit Frequency: Consider allowing only one mid-cycle adjustment per OKR, and only in the first half of the cycle.

5. Learn and Adapt: If you're frequently adjusting targets, your planning process needs improvement. Use this pattern as feedback.

Grading as Organizational Learning

The ultimate purpose of OKR grading transcends individual goal achievement. Rigorous, honest grading creates organizational intelligence that compounds over time.

Teams that grade seriously develop:

Improved Estimation: Pattern recognition helps teams set more accurate targets in future cycles.

Strategic Insight: Understanding what worked and what didn't informs broader company strategy.

Resource Allocation: Grading data reveals where to invest more resources and where to pull back.

Cultural Honesty: Organizations that grade candidly build cultures of transparency and continuous improvement.

Competitive Advantage: Companies that learn faster win. Rigorous grading accelerates learning.

Conclusion

OKR grading transforms goal-setting from performative exercise into strategic advantage. By mastering the 0.0-1.0 scale, understanding the philosophical differences between committed and moonshot OKRs, and avoiding common grading mistakes, your startup can build an execution culture that compounds learning over time.

Remember that the number matters less than the conversation it generates. A 0.4 grade that sparks insights about customer needs or technical constraints has more value than a 1.0 that teaches nothing.

The teams that win aren't those with perfect scores; they're the ones who learn faster, adjust more intelligently, and compound insights across cycles. Start grading rigorously, honestly, and collaboratively, and watch your organizational intelligence grow.